Trending Research
DAMO-YOLO : A Report on Real-Time Object Detection Design
In this report, we present a fast and accurate object detection method dubbed DAMO-YOLO, which achieves higher performance than the state-of-the-art YOLO series.
Ranked #12 on
Real-Time Object Detection
on COCO
OCR-free Document Understanding Transformer
clovaai/donut
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Current Visual Document Understanding (VDU) methods outsource the task of reading text to off-the-shelf Optical Character Recognition (OCR) engines and focus on the understanding task with the OCR outputs.
Multi-scale Multi-band DenseNets for Audio Source Separation
Anjok07/ultimatevocalremovergui
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This paper deals with the problem of audio source separation.
Multiview Compressive Coding for 3D Reconstruction
We introduce a simple framework that operates on 3D points of single objects or whole scenes coupled with category-agnostic large-scale training from diverse RGB-D videos.
On the Expressive Power of Geometric Graph Neural Networks
chaitjo/geometric-gnn-dojo
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The expressive power of Graph Neural Networks (GNNs) has been studied extensively through the Weisfeiler-Leman (WL) graph isomorphism test.
TorchGeo: Deep Learning With Geospatial Data
Deep learning methods are particularly promising for modeling many remote sensing tasks given the success of deep neural networks in similar computer vision tasks and the sheer volume of remotely sensed imagery available.
Utilizing supervised models to infer consensus labels and their quality from data with multiple annotators
Many algorithms also rely solely on annotator statistics, ignoring the features of the examples from which the annotations derive.
GLM-130B: An Open Bilingual Pre-trained Model
thudm/glm-130b
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We introduce GLM-130B, a bilingual (English and Chinese) pre-trained language model with 130 billion parameters.
Ranked #1 on
Language Modelling
on CLUE (CMRC2018)
GLIGEN: Open-Set Grounded Text-to-Image Generation
Large-scale text-to-image diffusion models have made amazing advances.
Ranked #1 on
Text-to-Image Generation
on COCO
A Simple Adaptive Unfolding Network for Hyperspectral Image Reconstruction
hustvl/saunet
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We present a simple, efficient, and scalable unfolding network, SAUNet, to simplify the network design with an adaptive alternate optimization framework for hyperspectral image (HSI) reconstruction.
